Numerous deep learning methods have been developed to tackle the challenges of
recognizing food images, including convolutional neural networks, deep feature extraction …

Common subspace learning methods only utilize local or global structure in feature
extraction, and cannot obtain the global optimal discriminative projection matrix. For this …

Graph convolutional neural networks (GCNs) with domain-specific feature aggregation
capabilities have unique advantages in hyperspectral image (HSI) classification. However …

Rainfall prediction includes forecasting the occurrence of rainfall and projecting the amount
of rainfall over the modeled area. Rainfall is the result of various natural phenomena such as …

Heatmaps are common tools in Explainable Artificial Intelligence (XAI) field, but they are not
without imperfections; Eg, non-expert users may not grasp the underlying rationale of …

Under the synergistic influence of global climate change and rapid urbanization, the
conservation of mangrove wetlands is facing great challenges. Accordingly, mangrove …

Data augmentation techniques have been useful in dealing with limited data for machine
learning tasks. Recently, spectrogram data augmentation techniques have been …

The representation of multimedia content experienced tremendous advances in the last
decades. Mainly supported by deep learning models, impressive results have been …

为了提升深度卷积神经网络设计的自动化程度, 并进一步提高细粒度花卉图像的分类准确率,
提出了一种改进的基于DARTS 的神经网络搜索方法, 用于自动构建细粒度花卉图像分类模型 …

Despite the great advances in the field of image classification, the association of ideal
approaches that can bring improved results, considering different datasets, is still an open …